| INORGANIC MATERIALS AND CERAMIC MATRIX COMPOSITES |
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| Study on the Pore Evolution of Pyrolysis Lignite via the Cubic Spline Interpolation Function Model Based on 1H-NMR Experimental Data |
| TENG Yingyue1,2, HOU Xingcheng1,2, BAI Xue1, LIU Quansheng1,2, LI Yi1,WU Kan1, ZHU Zhicheng1
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1 College of Chemical Engineering, Inner Mongolia University of Technology, Huhhot 010051, China
2 Inner Mongolia Key Laboratory of High-value Functional Utilization of Low Rank Carbon Resources, Inner Mongolia University of Technology, Huhhot 010051, China |
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Abstract The pores in lignite are important factors affecting their physical properties. In this work, the low field nuclear magnetic resonance (1H-NMR) technique was used to obtain the discrete data of the pore characteristics of lignite at different temperatures. Secondly, based on these discrete data, a cubic spline interpolation function model was constructed, and the new aperture distribution data different from the discrete data was obtained through the constructed function model. Finally, the new pore size distribution data obtained by the function model is compared with the experimental data, and the prediction accuracy of the function model was analyzed, the temperature threshold range is mainly investigated, and the reasons for the variation of the pore size distribution were analyzed from the physicochemical point of view. The results show that with the increase of experimental temperature, the pore structure of Shengli lignite mainly exists in the form of small pores (10—100 nm) and macropores (100—1 000 nm) below 200℃, micropores (<10 nm) and cracks (>1 000 nm) are mostly in the range of 200—500℃, and more cracks are generated at 715—950℃, which generally move toward the macropores and cracks. The function model can accurately predict the pore size distribution and temperature threshold based on 1H-NMR data. When predicting the overall pore size distribution of pyrolysis lignite, the root mean square error (RMSE) of the predicted value is small when the temperature is lower than 550℃, and the RMSE of the predicted value is larger when the temperature is higher than 550℃ compared with the experimental data. When predicting the proportion of pore size distribution of diffe-rent sizes, the error value of the micropore is only within 3.09%, the error of the small pore is within 0.85%—22.12%, and the error of the macropore is within 0.18%—7.95%. The ratio of the crack is within 4.43%, and the precision of forecasting is better. The model predicts that the temperature threshold of the pore size distribution of heat-treated lignite within 200—300℃ is 250℃, which is more suitable for the test results. The predicted temperature threshold of the model within 500—950℃ is 715℃, which is different from the temperature threshold of 700℃ obtained by the test results. It is caused by the model predicting the large RMSE of the overall pore size distribution of the heat treated lignite at 700℃. The model prediction results show that the cubic spline interpolation model has better prediction accuracy for the pore size distribution of different temperature pyrolysis lignite coal samples.
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Published: 12 September 2020
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| Fund:This work was financially supported by the Natural Science Foundation of China (21766023), the Natural Science Foundation of Inner Mongolia (2017MS0201), 2019 Science and Technology Project of Inner Mongolia Autonomous Region, the Innovation Experiment Project for College Students of Inner Mongolia University of Technology(2018086,2018064,2018074). |
About author:: Yingyue Teng, professor, master supervisor, doctor, Inner Mongolia University of Technology. Mainly engaged in energy and chemical industry, lignite clean use of theory and application research. Published more than 10 papers, undertook a Mational Natural Science Foundation, a number of provincial and ministerial projects.
Xue Bai, professor, doctor, master supervisor, Inner Mongolia University of Technology. Department of Inorganic Nonmetallic Materials Engineering, College of Chemical Engineering, majoring in inorganic nonmetallic materials/catalysis. She has undertaken two National Natural Science Foundation of China and published many papers on SCI and EI. |
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2020, Vol. 34 
